Leveraging artificial intelligence in economics and finance: Enhancing decision-making and market efficiency

Abstract. Artificial Intelligence (AI) has revolutionized the fields of economics and finance by providing advanced tools for decision-making, predictive analysis, and market efficiency. This paper examines the integration of AI technologies such as machine learning and natural language processing with mathematical models, specifically ARIMA for economic forecasting, Black-Scholes for option pricing, and logistic regression for credit risk assessment. By enhancing these models with AI, we demonstrate significant improvements in prediction accuracy and decision-making capabilities. Case studies illustrate a 15% improvement in GDP growth prediction accuracy, a 20% reduction in option pricing errors, and a 20% decrease in credit default rates. The paper also discusses the future prospects of AI, including advancements in quantum computing and ethical considerations like data privacy and algorithmic bias. Implementation challenges such as high costs and data integration issues are addressed, providing a comprehensive roadmap for organizations to effectively leverage AI. This study underscores the transformative potential of AI in shaping the future of economic and financial landscapes, driving innovation and operational efficiency.

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Publication Details

Journal
Applied and Computational Engineering
Published
2024-11-08
DOI
https://doi.org/10.54254/2755-2721/82/20240980
Citations
3
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
1.47
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article

Leveraging artificial intelligence in economics and finance: Enhancing decision-making and market efficiency

Daren Zhang
3 citations
Applied and Computational Engineering
Stock Market Forecasting Methods
1.47
article

Leveraging artificial intelligence in economics and finance: Enhancing decision-making and market efficiency

Daren Zhang
article en
3 citations

Abstract

Abstract. Artificial Intelligence (AI) has revolutionized the fields of economics and finance by providing advanced tools for decision-making, predictive analysis, and market efficiency. This paper examines the integration of AI technologies such as machine learning and natural language processing with mathematical models, specifically ARIMA for economic forecasting, Black-Scholes for option pricing, and logistic regression for credit risk assessment. By enhancing these models with AI, we demonstrate significant improvements in prediction accuracy and decision-making capabilities. Case studies illustrate a 15% improvement in GDP growth prediction accuracy, a 20% reduction in option pricing errors, and a 20% decrease in credit default rates. The paper also discusses the future prospects of AI, including advancements in quantum computing and ethical considerations like data privacy and algorithmic bias. Implementation challenges such as high costs and data integration issues are addressed, providing a comprehensive roadmap for organizations to effectively leverage AI. This study underscores the transformative potential of AI in shaping the future of economic and financial landscapes, driving innovation and operational efficiency.

Applied and Computational EngineeringVol. 82(1)
UNSW Sydney (AU)
Decent work and economic growth
Openalex Percentile: Top 15%
Stock Market Forecasting Methods
1.47
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Leveraging artificial intelligence in economics and finance: Enhancing decision-making and market efficiency — Daren Zhang · Applied and Computational Engineering (2024) | TGRS Research Map | TGRS